templatematch.cpp

// Declare your template and image
Mat* templ = ...;
Mat* img = new Mat(iplImg, true);

/// Source image to display
Mat img_display;
img -> copyTo( img_display );

/// Create the result matrix
int result_cols =  img -> cols - templ -> cols + 1;
int result_rows = img -> rows - templ -> rows + 1;

Mat result;
result.create( result_cols, result_rows, CV_32FC1 );

int match_method = CV_TM_SQDIFF;

/// Do the Matching and Normalize
matchTemplate( *img, *templ, result, match_method );
normalize( result, result, 0, 1, NORM_MINMAX, -1, Mat() );

/// Localizing the best match with minMaxLoc
double minVal; double maxVal; Point minLoc; Point maxLoc;
Point matchLoc;

minMaxLoc( result, &minVal, &maxVal, &minLoc, &maxLoc, Mat() );

/// For SQDIFF and SQDIFF_NORMED, the best matches are lower values. For all the other methods, the higher the better
if( match_method  == CV_TM_SQDIFF || match_method == CV_TM_SQDIFF_NORMED ) { 
    matchLoc = minLoc; 
} else { 
    matchLoc = maxLoc; 
}

// matchLoc is the top-left point of the bounding box